|
|
Absolute deviation, 绝对离差
& ^8 x0 h) }3 a1 nAbsolute number, 绝对数
& C5 C! A" o/ k+ z+ v+ WAbsolute residuals, 绝对残差$ r" [, q) P4 C3 w
Acceleration array, 加速度立体阵
- b1 T4 h0 U9 x: |7 M3 IAcceleration in an arbitrary direction, 任意方向上的加速度) E/ i! |9 x) X
Acceleration normal, 法向加速度' W6 N9 I; l% `1 g6 Y$ {* P
Acceleration space dimension, 加速度空间的维数9 W3 G* S4 u- V# M3 A* J9 r
Acceleration tangential, 切向加速度6 G$ R: Z* D( Z P5 ~. U
Acceleration vector, 加速度向量
* I8 \3 S9 b$ r: nAcceptable hypothesis, 可接受假设
% q& m" u. W p( kAccumulation, 累积2 X( ]" p: P. r& Z# G9 Z
Accuracy, 准确度3 p" d+ }& G' D- {+ v2 }
Actual frequency, 实际频数0 J% F/ p+ [0 I3 h* I
Adaptive estimator, 自适应估计量
# p2 S D$ X7 G9 p8 c3 U& nAddition, 相加% F5 W+ E8 ]9 p8 K/ N3 a7 t
Addition theorem, 加法定理
( A) Z" ^3 T5 w- N& B; {' f. mAdditivity, 可加性
* b3 _5 @& R# r. \Adjusted rate, 调整率7 x4 M5 ~: r( I2 E7 Y0 o& v" Y
Adjusted value, 校正值$ ^3 [( n3 U$ A/ b! e
Admissible error, 容许误差
) _ K* E3 k r2 `# RAggregation, 聚集性
: h( D( e- ]% i2 Q% ?Alternative hypothesis, 备择假设
) E4 Y+ H& z0 w" L1 gAmong groups, 组间
% J0 k+ h/ D7 oAmounts, 总量
2 N4 U% k1 e H# W: ^4 }8 ?/ gAnalysis of correlation, 相关分析
2 a& p: u m0 d+ @% l& l9 rAnalysis of covariance, 协方差分析8 z7 `3 Y1 \" c% @- u. L; G
Analysis of regression, 回归分析
& L2 n# Q$ n! Z! G, Y7 y+ ^$ q# @* u$ ]Analysis of time series, 时间序列分析
0 r1 v) E1 l/ k( XAnalysis of variance, 方差分析3 K$ P, M- I* {
Angular transformation, 角转换/ G8 |7 ~" M! Z; c2 J, a" C5 ~
ANOVA （analysis of variance）, 方差分析
5 t1 Y$ j: H0 o# C& R; E: ZANOVA Models, 方差分析模型
: a: |, T. ]# G2 S; m& cArcing, 弧/弧旋
% @- q7 H* g$ X5 q1 T/ h( jArcsine transformation, 反正弦变换
0 O! C4 n# v. ?- y9 GArea under the curve, 曲线面积$ g& p& n5 Z& A" \, @0 r% [/ H
AREG , 评估从一个时间点到下一个时间点回归相关时的误差
" @0 i, \8 t( BARIMA, 季节和非季节性单变量模型的极大似然估计 P2 }) G7 L, o: C* V! h5 d
Arithmetic grid paper, 算术格纸
! L. v! U' M8 j& Q' s, RArithmetic mean, 算术平均数
* }8 g' I' }( E7 HArrhenius relation, 艾恩尼斯关系, h1 d' y$ H4 u* h/ B
Assessing fit, 拟合的评估3 ~& `: g8 w0 ^
Associative laws, 结合律/ \+ C# @( O& p* M
Asymmetric distribution, 非对称分布. ?; ]) P% M: R% r
Asymptotic bias, 渐近偏倚2 n4 m9 ]0 e0 m: x; G% `8 D! t
Asymptotic efficiency, 渐近效率
) G( U+ P( W/ cAsymptotic variance, 渐近方差- v% L1 A" p1 C5 }; q1 D: z( K
Attributable risk, 归因危险度
5 U/ h/ ?. r$ \( Q `3 O3 R5 `, KAttribute data, 属性资料; K6 R6 P6 c6 X: Q, V4 g1 v
Attribution, 属性* ^. l3 L/ v' F! e. t. {
Autocorrelation, 自相关
3 C& `+ u) g: _) x5 l8 ]' pAutocorrelation of residuals, 残差的自相关! R$ U. S2 V- R/ w$ o" L
Average, 平均数 f* B5 U, Q3 y. x
Average confidence interval length, 平均置信区间长度
( b2 H3 X4 e2 w: n1 ~# @+ K$ l( xAverage growth rate, 平均增长率
; v* `5 n& q+ ~# O PBar chart, 条形图" r4 O2 M: P: {2 y# U/ O. O3 G( Z/ @
Bar graph, 条形图
! B, i% p' e1 q3 Q& KBase period, 基期! ]: e' _5 O. w. C5 o- W
Bayes' theorem , Bayes定理4 j+ w |1 \; ^7 G, G# |* v
Bell-shaped curve, 钟形曲线
8 k9 y! }' S9 j2 \- l* Y& x, ~Bernoulli distribution, 伯努力分布
" }% h8 i$ n, k# NBest-trim estimator, 最好切尾估计量
5 ?0 y5 G" I5 }! b U* N# W3 RBias, 偏性! Q3 V" u7 P8 x. d) V9 k5 M: [
Binary logistic regression, 二元逻辑斯蒂回归
1 \1 ~% }3 c2 D, x' T0 |Binomial distribution, 二项分布& i/ P& w. q5 e9 w9 w
Bisquare, 双平方. q6 l9 m' k3 M. s1 r( h; P, D
Bivariate Correlate, 二变量相关$ h7 J4 d3 c9 C' U! ~
Bivariate normal distribution, 双变量正态分布% O a) c+ z9 ~: d) J+ {
Bivariate normal population, 双变量正态总体
- T+ {+ T% G' q( H$ @' F; e1 LBiweight interval, 双权区间
$ T; b) Z- R4 _Biweight M-estimator, 双权M估计量' y$ ]* S7 d! L
Block, 区组/配伍组
, P' U5 o) B* FBMDP(Biomedical computer programs), BMDP统计软件包) j' d/ f! I( }8 b; P; @
Boxplots, 箱线图/箱尾图0 J y& _0 N! G. {' E# g: t- s. n, {
Breakdown bound, 崩溃界/崩溃点
6 T+ A% B$ o3 J# l( q" ?Canonical correlation, 典型相关. c. i& D, R$ |# ^7 O, T
Caption, 纵标目9 P' a# H4 m' A& Q8 N( f. J$ a5 _
Case-control study, 病例对照研究
8 {7 M$ k) q9 UCategorical variable, 分类变量
) A* @2 _) I8 b) y9 VCatenary, 悬链线5 I% B; B0 [9 j4 C6 a. E
Cauchy distribution, 柯西分布
4 L* N+ I7 i8 `$ E) V! B4 M$ lCause-and-effect relationship, 因果关系% M: S( F! x: M- [4 @6 l
Cell, 单元% L' t$ h2 T, Z
Censoring, 终检
2 b @; D- p+ e1 v5 s9 u0 \Center of symmetry, 对称中心
- ~6 ]6 `6 h5 F \* DCentering and scaling, 中心化和定标- N3 t# Z8 r0 N" g1 B
Central tendency, 集中趋势
3 g& {% e+ `" g- dCentral value, 中心值- M! l/ Y3 n' z' _
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
. S! b/ ]# d* O4 w3 Q5 zChance, 机遇/ U* k4 q+ c6 s" u; g. }' g
Chance error, 随机误差
6 Q3 y# l) e4 YChance variable, 随机变量
+ V! b9 w3 x' z4 w) W1 _Characteristic equation, 特征方程0 R! q! `8 e. o+ j1 _
Characteristic root, 特征根
5 M7 m7 A# l. y- u% o( H& [9 q ^5 j% ZCharacteristic vector, 特征向量
: r( `' m! a# l" c. ~Chebshev criterion of fit, 拟合的切比雪夫准则- ]; T r& F: C1 U) V4 n1 R
Chernoff faces, 切尔诺夫脸谱图
) ^0 ]! d) t4 ?$ I* TChi-square test, 卡方检验/χ2检验
" ~& a. U+ n4 k& }- B. ECholeskey decomposition, 乔洛斯基分解
6 Q* D5 M& Y p& }Circle chart, 圆图
7 g. s. N5 n/ h) r( PClass interval, 组距* N/ ~: O/ L/ S/ \: q* X# c: ^* J% s
Class mid-value, 组中值3 n( m, X, N9 N7 X
Class upper limit, 组上限; W, f# a: E: M! W& h
Classified variable, 分类变量
+ g+ F! ^2 C. ~" G9 r& qCluster analysis, 聚类分析
& r9 x5 Y6 c0 e! y* `5 DCluster sampling, 整群抽样: s: L, V5 Q/ U3 \" c& |
Code, 代码* m% G p' J/ h9 R
Coded data, 编码数据
! T+ N) m$ ^/ V/ Y+ E2 z( @( g' xCoding, 编码; Y& M' g6 K( s
Coefficient of contingency, 列联系数
1 C# L4 F' Q3 R; z2 k V) ~Coefficient of determination, 决定系数
% z" g& L8 V7 L! r9 nCoefficient of multiple correlation, 多重相关系数- [% u. y$ y0 i4 z
Coefficient of partial correlation, 偏相关系数% P7 \; N. E5 x- @/ u+ \
Coefficient of production-moment correlation, 积差相关系数
1 k& R9 ~; X: ]- q4 s, sCoefficient of rank correlation, 等级相关系数# Y7 A& c) N: J
Coefficient of regression, 回归系数
. V1 n9 z, V6 A6 \Coefficient of skewness, 偏度系数
$ U6 Y" O/ P: q p6 i' \' d. V$ LCoefficient of variation, 变异系数
6 D% z) Q% Y a% G' e5 G' [+ rCohort study, 队列研究 `% |. r# S" Z {# c
Column, 列* Y# ^* u* j. F& N, f" d/ ?
Column effect, 列效应
8 B. S& |' ?& q. QColumn factor, 列因素
" a& ^% e7 o) d B) U6 F' DCombination pool, 合并 y5 s4 i% b2 r6 V" E5 Z) B
Combinative table, 组合表+ @( ?) Y& ~. T( d
Common factor, 共性因子5 G: I8 a1 A) ~! _9 z
Common regression coefficient, 公共回归系数
) L& J5 v' N! @6 CCommon value, 共同值
! h6 b% a# ]( t) E; d$ r# QCommon variance, 公共方差
2 p, R, b( K4 R, G: t3 g: U5 yCommon variation, 公共变异
3 O& N1 [1 z+ C$ A0 Q9 PCommunality variance, 共性方差5 d+ c/ C7 t" S* J8 R# B& ?4 Z
Comparability, 可比性
0 n0 C" v) }( b6 j' |! t7 e% TComparison of bathes, 批比较
/ b. ~# E3 [. Z+ n) }& `' MComparison value, 比较值; P7 O7 @. O+ ?* x( I" ~
Compartment model, 分部模型
; A# _0 E4 ?: {+ s! \7 LCompassion, 伸缩# Z N7 k4 I2 V5 e) [/ U
Complement of an event, 补事件" x% X- u4 v" {: Q
Complete association, 完全正相关0 o ?/ y# D4 U' C2 b4 d% g
Complete dissociation, 完全不相关
- \; g. V8 C B8 ]3 \& sComplete statistics, 完备统计量
. u+ v% ?" `0 MCompletely randomized design, 完全随机化设计2 v% k' @1 y. Q
Composite event, 联合事件% V2 y( V4 E. P5 W: y8 e. I% M" y
Composite events, 复合事件' Z0 h6 e+ c. `; |
Concavity, 凹性
/ a4 Z' c, R: I/ nConditional expectation, 条件期望
& d+ B* j2 @: B# i9 ^2 DConditional likelihood, 条件似然
5 s' f8 O8 w2 D* _" BConditional probability, 条件概率2 X0 n" T. q4 F" {6 m) I O2 K
Conditionally linear, 依条件线性
j; K& K1 V) g: a [4 B3 D! KConfidence interval, 置信区间. v9 n) u9 Q1 q$ h, x
Confidence limit, 置信限" a7 @6 d8 n+ |1 X' q
Confidence lower limit, 置信下限) O- R; c1 e4 f
Confidence upper limit, 置信上限6 D8 @/ {6 V8 l4 P7 _% g# k, X
Confirmatory Factor Analysis , 验证性因子分析8 O3 F* w$ _3 D9 o/ \; c8 m
Confirmatory research, 证实性实验研究
9 o! r6 t4 @8 [& dConfounding factor, 混杂因素7 Y) Q# }# J$ A. { {* s
Conjoint, 联合分析9 E0 `( j0 }; m* f
Consistency, 相合性( P$ ~0 |2 J& n4 n( ~
Consistency check, 一致性检验) f% A2 \% ?4 G$ {) k
Consistent asymptotically normal estimate, 相合渐近正态估计1 [4 F3 W) O) P$ ] W
Consistent estimate, 相合估计. z* L& G6 C r8 \
Constrained nonlinear regression, 受约束非线性回归
) ?4 [6 f" z1 W/ k. D9 P* ^$ }Constraint, 约束
. y8 {0 L- s! Z- k: C& I" \4 c! QContaminated distribution, 污染分布5 S& f) d. \$ B7 g4 X
Contaminated Gausssian, 污染高斯分布% V, x0 c6 L; f: Y& E& Z2 f/ W
Contaminated normal distribution, 污染正态分布
3 J( n5 T6 R" S) w7 _) `Contamination, 污染
: f9 @: c; U( ^. s, f- ]- u- `# {Contamination model, 污染模型
" l9 \% k' {% D# g5 B, g: fContingency table, 列联表
7 x4 x5 g- [) _: i6 sContour, 边界线
" l8 L, N! M7 h4 T! t) z aContribution rate, 贡献率" h, }' H+ O/ _7 u
Control, 对照
& A% z& K4 Y' }9 B8 I9 gControlled experiments, 对照实验2 r5 l' }+ V5 E1 p- \' m
Conventional depth, 常规深度3 e: g6 ?0 e9 s* Z# w3 Z' h, \6 A
Convolution, 卷积
r% u- g5 M9 B: o2 HCorrected factor, 校正因子
) V0 c/ j' Q$ r! {3 _) yCorrected mean, 校正均值
( p# R# W, Y/ ?7 U- E5 g" KCorrection coefficient, 校正系数4 o8 y6 N; |' Y& R w+ i! f! D
Correctness, 正确性6 d6 P- T1 @9 i% w2 O4 n; c o
Correlation coefficient, 相关系数
- ]" c' x# Z% _/ k! SCorrelation index, 相关指数
`# P5 Z" Y& NCorrespondence, 对应
. i! d, y6 {) R1 Y' h/ n) ^ F. q8 Y6 PCounting, 计数
$ V! Q0 p* _8 h* SCounts, 计数/频数
; l7 J# b2 \; ^+ YCovariance, 协方差
; E u5 G( N9 I4 eCovariant, 共变
. [: X, }8 V6 m: ]6 N, |4 cCox Regression, Cox回归6 Y0 u1 j$ V5 [9 z( ]7 T$ ^# Y
Criteria for fitting, 拟合准则2 [' C) \$ q, j+ C# F
Criteria of least squares, 最小二乘准则5 g. s3 p1 ^# }- \# K0 @
Critical ratio, 临界比+ |0 w7 L! \9 \) F3 M2 G, Q7 ?" a9 H
Critical region, 拒绝域( w6 b, A' j( t8 u7 M7 W2 r/ Z1 J9 p* c
Critical value, 临界值* l6 ?9 n; M" ?" O5 p9 |* N
Cross-over design, 交叉设计% ]* O: H& G; f" d) T" w
Cross-section analysis, 横断面分析
+ d, O& p' C$ p; c% TCross-section survey, 横断面调查
; S6 h9 ^; C4 A0 v( ~Crosstabs , 交叉表
" O) ?7 M, `/ G$ R9 _$ E3 ?: z7 {Cross-tabulation table, 复合表
3 @8 U3 f, B* H0 }Cube root, 立方根
& C6 c, T6 {. N# c+ m& `Cumulative distribution function, 分布函数
1 L; C* V7 w. T+ k7 \Cumulative probability, 累计概率
0 F- a8 v3 ^3 z2 {- |6 n% qCurvature, 曲率/弯曲; D2 p4 G ?3 s0 ]) X! j
Curvature, 曲率- Z1 b$ r' E, F# g9 d
Curve fit , 曲线拟和 7 x O% s8 I& A
Curve fitting, 曲线拟合8 i! G6 y* ^6 e: n) w& `5 J
Curvilinear regression, 曲线回归! j8 a5 W* k. F* B S9 p8 K
Curvilinear relation, 曲线关系2 l c) q6 k1 V5 t, y! W
Cut-and-try method, 尝试法+ h: Z o- T- k6 i5 C( R' v
Cycle, 周期2 c/ ^/ P* ~, T: S j
Cyclist, 周期性' G+ P* x6 w z% p/ ^8 q) D
D test, D检验) r ~2 s; ?0 m' y$ G
Data acquisition, 资料收集
- V$ y( x; |& d: Q& {8 `Data bank, 数据库/ Y4 p( w: ?+ \$ G# T
Data capacity, 数据容量2 |, n, H; [, y$ f7 z
Data deficiencies, 数据缺乏
8 Q0 C! T- V% o( K5 YData handling, 数据处理, I6 g' d# e! V y
Data manipulation, 数据处理
; X3 g/ j0 U/ F+ _* n5 u" WData processing, 数据处理
# a g4 b4 [1 R! w3 ~ a$ d' dData reduction, 数据缩减
+ W/ i2 l Z7 D8 P7 F9 H0 c b5 xData set, 数据集
4 G! R& h$ C1 u' }Data sources, 数据来源) f6 C8 c& H/ H& y# `
Data transformation, 数据变换
" Y5 }0 A" @. \; T& Z. j. z" S- ]9 OData validity, 数据有效性
) G( a! ?8 R" ?9 D" M* w3 n' MData-in, 数据输入6 a/ O" }8 x8 i% _' S. y3 ?+ g
Data-out, 数据输出
8 a/ V6 w) e3 o3 x0 E4 l+ XDead time, 停滞期
& P, P l# ^6 i: o' W3 WDegree of freedom, 自由度
5 A; z+ t2 z3 j1 \Degree of precision, 精密度
0 \2 F* C; O. a! w s3 P8 SDegree of reliability, 可靠性程度& v& m8 K3 b6 |* a* l4 T
Degression, 递减) F# ^% e6 e7 B6 f
Density function, 密度函数
: N2 n. T% Z: }1 u3 Z; C6 i( CDensity of data points, 数据点的密度
5 a% Z/ {, `* p5 U9 l1 y3 O' e7 dDependent variable, 应变量/依变量/因变量' U0 ?/ c& z1 i9 K1 n6 p+ D
Dependent variable, 因变量: `% a5 I! W& o, g
Depth, 深度
! X' t! g ^6 ^- qDerivative matrix, 导数矩阵7 }8 ~! ^/ N8 u1 O0 T/ o" g
Derivative-free methods, 无导数方法
2 x5 a3 h7 n, N, LDesign, 设计& p1 B. @5 D! q, J3 h+ M
Determinacy, 确定性6 {' j/ l0 z2 @& c
Determinant, 行列式
7 z/ G4 k* J7 cDeterminant, 决定因素5 U- C* g. i: V8 {
Deviation, 离差4 l6 N6 c: p) [+ x% G
Deviation from average, 离均差
' r2 `3 S) f0 \; E. }, x0 U; D; j! UDiagnostic plot, 诊断图2 X. A" l$ {! R; J7 Y' v( z7 _8 Q' T
Dichotomous variable, 二分变量
$ s- F! A2 ?5 r5 C" T6 U ZDifferential equation, 微分方程
! w1 ~2 T' ]" |0 u4 R8 p5 T F8 MDirect standardization, 直接标准化法
# o5 `" F; b( ?- y7 L$ |Discrete variable, 离散型变量
5 A9 B1 x3 q! Q6 ?* H) lDISCRIMINANT, 判断 % Z! U$ l- ~+ T M
Discriminant analysis, 判别分析
W1 r1 R% v8 {2 ~* H0 YDiscriminant coefficient, 判别系数
, V" C$ Q, o9 _% }Discriminant function, 判别值, \; v6 {/ h1 d
Dispersion, 散布/分散度: _, a9 W4 k; F$ L r9 s& p" u
Disproportional, 不成比例的# ^) t' m% p0 ]% V l; m* n' @2 F
Disproportionate sub-class numbers, 不成比例次级组含量
P) Q( N6 K) ?4 `! f2 M& l/ j" RDistribution free, 分布无关性/免分布3 l- R2 Z* I4 v. F6 _, p9 M
Distribution shape, 分布形状( B& t7 y% g- F, W6 m
Distribution-free method, 任意分布法9 i6 P& ?! g1 ^% j; Z
Distributive laws, 分配律3 C; R3 J: k+ z& J/ }1 k
Disturbance, 随机扰动项
# C+ K! s) K) B" G; EDose response curve, 剂量反应曲线
& ^; |, M! T' O6 G4 rDouble blind method, 双盲法! y% `' h3 u' ?4 U- s
Double blind trial, 双盲试验
# ~4 s" M1 T1 k* t( \, i1 S/ Z8 w9 FDouble exponential distribution, 双指数分布
! a4 {, J. o" ]% t8 [4 i7 RDouble logarithmic, 双对数, v9 y, r* |: d+ L# L
Downward rank, 降秩
6 U" n* ~* i) {; lDual-space plot, 对偶空间图
: o1 ?" a; t1 t# JDUD, 无导数方法7 L5 u* ~* j5 g' G
Duncan's new multiple range method, 新复极差法/Duncan新法
% l7 q% D/ D n# iEffect, 实验效应$ @& f. W R! h7 [: Q7 L4 ?
Eigenvalue, 特征值3 o/ |! G( h; `, f
Eigenvector, 特征向量
- @& w' U$ O8 x- |Ellipse, 椭圆
/ M6 o- e! q% fEmpirical distribution, 经验分布
# z' t" A/ L7 s- s% I9 ?. n* N* SEmpirical probability, 经验概率单位
/ w# o5 r) d; l6 N" QEnumeration data, 计数资料6 e, F m3 D: Q- C% B
Equal sun-class number, 相等次级组含量
2 n+ g" c. E& z Z# WEqually likely, 等可能; F% e3 x, ^; X. G' O5 a! T
Equivariance, 同变性
- S- H, ^- H) x5 YError, 误差/错误
8 v- P% J4 Y/ i( |Error of estimate, 估计误差
8 T3 b( }' P. ~; A. U; xError type I, 第一类错误' \! ~( `! a3 c" k, W
Error type II, 第二类错误3 k, C8 _4 i9 l7 I) n8 U
Estimand, 被估量7 e& z/ G( ~! P! a3 a
Estimated error mean squares, 估计误差均方# U1 M# s9 {8 f9 I' E. b
Estimated error sum of squares, 估计误差平方和
2 E$ L; l" ?; O! f! EEuclidean distance, 欧式距离
7 o6 V: |: p* L0 ^ y: P% hEvent, 事件
* M% f$ k: e% o2 N. ^: xEvent, 事件
r) g- S$ @! ^6 r6 mExceptional data point, 异常数据点, v2 ^, u }% S- O: l9 E# |: M7 K
Expectation plane, 期望平面
0 @1 Y- D& u2 w; K8 J+ S3 \1 jExpectation surface, 期望曲面, D- h8 @; }9 e( j- W' ~1 I
Expected values, 期望值$ A# h9 Q: K! U
Experiment, 实验0 k, @, ^+ H1 p( E/ ~. y
Experimental sampling, 试验抽样
: \; [9 `: d6 c' g o4 F5 F( zExperimental unit, 试验单位
6 ~. w) i9 w% f! X, mExplanatory variable, 说明变量
! m/ A- ]+ e B9 s Q6 jExploratory data analysis, 探索性数据分析. S' @1 @0 s9 A( ~% r$ Y
Explore Summarize, 探索-摘要$ l+ H" L/ G5 R- ~
Exponential curve, 指数曲线
, Q4 ]( Y+ u W4 m- h# G hExponential growth, 指数式增长' n6 H( T2 u" X8 N0 G
EXSMOOTH, 指数平滑方法 5 s& Z+ T* A2 o" Q: ~
Extended fit, 扩充拟合& B. j, t: w; i" I+ S
Extra parameter, 附加参数
: @7 o% F8 k. X) C9 S$ R' e! `6 fExtrapolation, 外推法& ^6 I. w# i7 G, X! W8 O, E
Extreme observation, 末端观测值" j, @4 l2 ]5 J" _ [8 a/ n
Extremes, 极端值/极值, W1 l" K% ^9 p q9 f' ~8 r& k% e# K
F distribution, F分布
" v; U ?, f; |F test, F检验
: [/ c8 g; X0 c( O" k8 C2 {Factor, 因素/因子- V: J) _# {6 V1 G- V
Factor analysis, 因子分析6 A; w# j: k2 E! a
Factor Analysis, 因子分析
: l0 I6 n6 D% W5 q5 ^/ VFactor score, 因子得分
' ]6 Y. b3 T7 F7 h: Z& dFactorial, 阶乘' z7 v2 j1 e7 C( ]( l: Q) ~
Factorial design, 析因试验设计
4 M3 q* `2 c- N( m( W5 _ |0 k {False negative, 假阴性
4 h L2 Y& ~) z" R0 [ n( U3 eFalse negative error, 假阴性错误3 W. ` K( o: P( i w; \7 u* o
Family of distributions, 分布族, q2 s6 D0 D7 f5 y; L
Family of estimators, 估计量族
' {( W9 H0 n0 K0 y( `& d: m% @Fanning, 扇面$ W) W' m7 v: W0 M
Fatality rate, 病死率
# V7 S- X; g1 C, O4 oField investigation, 现场调查9 x) t) z: O" d
Field survey, 现场调查
. Y8 H( M0 [: n0 J+ I& tFinite population, 有限总体
$ _+ N7 D/ q N& N- L) B3 B) dFinite-sample, 有限样本) V, w2 T3 b3 b
First derivative, 一阶导数
2 O+ U5 u; b0 Z/ x/ ~( m. OFirst principal component, 第一主成分+ W! ?8 m" e9 j* N" y `
First quartile, 第一四分位数2 a" o- h7 Q! ]5 V$ |! _) E5 A- d
Fisher information, 费雪信息量. P9 R0 A% s- H* M8 @( K
Fitted value, 拟合值+ k( ] ]" f& t
Fitting a curve, 曲线拟合
" F$ Y" G3 J( H- L- c( A. }Fixed base, 定基9 f2 {- n* X0 U" F$ u
Fluctuation, 随机起伏0 ^1 j$ m: r9 D! ^" m( `( t
Forecast, 预测
' K# E9 [2 o* S: tFour fold table, 四格表& U9 P4 ?5 Z, w1 Q
Fourth, 四分点
2 p1 _) }; X( m7 [4 JFraction blow, 左侧比率
& ~, n- ^$ x; b; v0 aFractional error, 相对误差
4 x6 L6 Q" B$ R2 q7 uFrequency, 频率
1 G1 }" e) O' o/ [# f5 u' G3 NFrequency polygon, 频数多边图6 k' C" K& F* v9 r- v+ U
Frontier point, 界限点
- H7 [3 z' v8 S' R7 E' \Function relationship, 泛函关系% g& y- ^$ m I" O
Gamma distribution, 伽玛分布3 t3 u# a) n( W* e
Gauss increment, 高斯增量
& Q* o% R# h: z* G% o% |Gaussian distribution, 高斯分布/正态分布
! T6 r* A8 O$ J$ S' b% Q) yGauss-Newton increment, 高斯-牛顿增量( I8 v4 r% _/ { d8 [
General census, 全面普查
" t0 l8 Y, |% P8 Q! Y7 x# u$ A2 fGENLOG (Generalized liner models), 广义线性模型 8 H0 J: X9 Q, V2 e
Geometric mean, 几何平均数4 b2 _# p& l! x! e+ d3 Y
Gini's mean difference, 基尼均差/ a( [3 B( z* B) O
GLM (General liner models), 一般线性模型 4 y( E# e, _) W3 E0 n2 h; \' G
Goodness of fit, 拟和优度/配合度+ `8 i# x; f8 B0 ~4 l2 m7 J2 B
Gradient of determinant, 行列式的梯度
1 o0 [3 H% ]1 k \3 M# {# ]6 fGraeco-Latin square, 希腊拉丁方0 |0 [+ Q. }4 p6 L, W" ~
Grand mean, 总均值2 `3 `9 g: T/ w9 y- m
Gross errors, 重大错误8 V3 r3 _3 Z5 l- i3 T& i
Gross-error sensitivity, 大错敏感度
3 ~% y" Z, M4 ~6 h: x6 bGroup averages, 分组平均
' z' P& o. {4 ]' t7 rGrouped data, 分组资料+ O$ z/ O: K/ u) W' {
Guessed mean, 假定平均数
- C+ A; K# s! g+ C, ]Half-life, 半衰期
2 F3 w" h6 B1 E+ r3 B; UHampel M-estimators, 汉佩尔M估计量
6 u; O7 V% M2 x, i/ u6 o5 JHappenstance, 偶然事件. P9 x) {7 {3 [( J+ U/ G: ~* M$ A2 R
Harmonic mean, 调和均数
6 Y" F# M p. E0 gHazard function, 风险均数3 q. z# _4 |5 h4 V# c
Hazard rate, 风险率
8 f$ Q$ B# D0 K1 h; eHeading, 标目 : F, |0 V7 {. m! w
Heavy-tailed distribution, 重尾分布5 s. H$ K$ b7 P/ W! D% P
Hessian array, 海森立体阵, O( ]0 {* P$ c( n' d6 f7 m
Heterogeneity, 不同质0 k2 W: [1 Y. k: J" Y% g1 x
Heterogeneity of variance, 方差不齐
0 l8 e2 U% V: B2 z8 _Hierarchical classification, 组内分组" |1 w2 C" A) \; U$ t! g+ u: a
Hierarchical clustering method, 系统聚类法
. h/ O7 A0 J _6 {High-leverage point, 高杠杆率点9 A3 Y5 ^7 ~4 Y% V; ?
HILOGLINEAR, 多维列联表的层次对数线性模型6 v8 `4 K, Q& R2 N
Hinge, 折叶点- l, u/ ^/ f, P* h8 w
Histogram, 直方图) ?9 n$ ?- @/ J& d3 r# z
Historical cohort study, 历史性队列研究 2 b2 @5 W5 z7 Q8 }5 o2 p9 E
Holes, 空洞
) I6 r4 s- a8 U% tHOMALS, 多重响应分析
% h3 P- ~4 ^# F9 h- PHomogeneity of variance, 方差齐性. H D. w* e4 p* m! ?) @+ B
Homogeneity test, 齐性检验
# x* g3 e% ~' e" t+ p' Z7 l, IHuber M-estimators, 休伯M估计量1 e+ m( y2 |' p4 ]" T4 r
Hyperbola, 双曲线
' F* }) c9 I" H* R T( B+ ?8 A7 {, N7 J$ IHypothesis testing, 假设检验
4 S, x. H" O" [5 {+ T1 R* BHypothetical universe, 假设总体7 q! `) Q6 A. w0 D
Impossible event, 不可能事件
+ \; V# L$ R4 G( N2 i! k( CIndependence, 独立性
2 T8 X4 k8 e6 OIndependent variable, 自变量* U$ I+ W& A0 k) ^- o( ^3 E
Index, 指标/指数
2 J- E& R8 i' C2 M( ]; H: m7 mIndirect standardization, 间接标准化法( S* j' l3 p0 e7 N' N1 F1 b- U
Individual, 个体
* V; t, L" c* }; j& v, E7 wInference band, 推断带9 V, @: k+ a/ ^4 s+ @# g8 a; X/ P
Infinite population, 无限总体
- G- Z& Z- [4 a; d1 A& nInfinitely great, 无穷大4 i) c! `" l/ ?+ @& ~$ D+ k
Infinitely small, 无穷小9 K, d2 Y" F9 ]' b
Influence curve, 影响曲线, p9 _: `, @- n% @' m" t8 ?
Information capacity, 信息容量3 A/ y. k1 U3 x5 _
Initial condition, 初始条件
* A7 q3 o1 R/ N) |Initial estimate, 初始估计值
9 \6 I+ I# F0 Y1 VInitial level, 最初水平
1 J5 i1 K1 m! e& HInteraction, 交互作用
; I# d- g. i) r% B4 @4 zInteraction terms, 交互作用项5 f3 f" u5 p8 I' \& ] ^
Intercept, 截距* l3 U$ N" T, _$ f+ [7 ~+ ~0 _
Interpolation, 内插法
! G3 `4 H. p- z$ M6 @; U$ `Interquartile range, 四分位距
, X- n* ]" ]+ JInterval estimation, 区间估计
1 }# e* j% l/ m+ h- J$ zIntervals of equal probability, 等概率区间. A! Y0 [ z+ r% M- H, R: x
Intrinsic curvature, 固有曲率& n- g9 Q z; S" L5 b" e4 b
Invariance, 不变性9 x. _+ O \* b6 C. q
Inverse matrix, 逆矩阵1 ~5 e Y3 j' q; V2 w: X
Inverse probability, 逆概率8 Q4 o3 g/ y' K% Y0 u
Inverse sine transformation, 反正弦变换
$ o( [1 O- P1 k9 l- s; M' d5 ^Iteration, 迭代 : |3 s/ E8 T5 M1 a% _& b! x1 K
Jacobian determinant, 雅可比行列式- M4 D/ ]3 _$ H( m! C. J0 E/ S
Joint distribution function, 分布函数" ?3 l; |+ l* j9 L9 x
Joint probability, 联合概率
' @ `7 B7 r" ^: i3 AJoint probability distribution, 联合概率分布) r( _- m5 ?( I
K means method, 逐步聚类法. u+ [) ^7 m1 O+ j# p: c
Kaplan-Meier, 评估事件的时间长度 / X, I, \* E# w0 d, h2 I
Kaplan-Merier chart, Kaplan-Merier图
0 }/ S5 S$ C" T; w4 X$ T3 a* zKendall's rank correlation, Kendall等级相关$ }5 [ l# n. H' A$ w5 a
Kinetic, 动力学
4 J0 W/ v! M7 JKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验; q6 k% J6 H" R, O
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
' L9 h; y' D5 t& q1 P3 \. ?Kurtosis, 峰度
* T( I/ N1 H8 G0 R! t. a" TLack of fit, 失拟
' e7 I0 k& `* h2 |1 _& j5 o9 I( OLadder of powers, 幂阶梯* L9 V! L. G9 b2 V4 h" G& {9 ~% [
Lag, 滞后5 u3 R3 k& W! c- \& E: O
Large sample, 大样本
r7 _. c, F2 z4 M$ RLarge sample test, 大样本检验4 X& S- O/ g. l; e. b5 Q
Latin square, 拉丁方
( l/ C" o% b+ d5 X' b8 d9 sLatin square design, 拉丁方设计
H6 r% F4 |; `0 a" l' ELeakage, 泄漏
% r, d$ i0 e2 b* tLeast favorable configuration, 最不利构形
8 W( |$ j n/ T5 LLeast favorable distribution, 最不利分布/ A% [" P5 @9 T" _& Q; N8 s8 x) k
Least significant difference, 最小显著差法
9 G+ K) f$ G+ J& `% a+ g$ ILeast square method, 最小二乘法
! r4 U4 F; b% {6 m& MLeast-absolute-residuals estimates, 最小绝对残差估计
( T$ b7 i. y6 c; U3 aLeast-absolute-residuals fit, 最小绝对残差拟合
9 v8 e' p( x2 V4 h5 W/ P1 u$ YLeast-absolute-residuals line, 最小绝对残差线9 k4 o- v* n2 x
Legend, 图例2 I# S/ t* O7 G% D1 K- I7 T- i" U
L-estimator, L估计量9 @+ G- {$ a; I5 i. G2 }; R1 G
L-estimator of location, 位置L估计量2 X" r5 w9 ~' s- t
L-estimator of scale, 尺度L估计量. U$ o* x% f7 b# b; c
Level, 水平7 j L5 ]# [( ?( \* {7 B
Life expectance, 预期期望寿命
! V- {! o) G' _0 J! l& TLife table, 寿命表
* I) s/ u# H! D: {% n7 |" DLife table method, 生命表法- B% z. E" P& c$ v( R
Light-tailed distribution, 轻尾分布
2 O( q3 T P6 q& e+ l4 QLikelihood function, 似然函数( L( l8 v4 u6 x9 F& z- _
Likelihood ratio, 似然比
5 d4 i2 \1 n2 v- Q! s6 xline graph, 线图
: n2 e2 a$ Q! I! E4 n0 L9 _- R8 n* bLinear correlation, 直线相关6 r9 F* U6 q8 w) L
Linear equation, 线性方程
" Q; A6 o4 K$ x( z5 j5 ], C$ eLinear programming, 线性规划! Y# ]/ z0 B+ `! `
Linear regression, 直线回归
- V1 `1 b: z5 u0 a) |3 ^Linear Regression, 线性回归( J) N% c+ d/ |4 [# O' {
Linear trend, 线性趋势; u/ V% Q- a4 C' @, F
Loading, 载荷 7 l/ F# ^9 w* x
Location and scale equivariance, 位置尺度同变性
# h* T, |- K1 k% ~8 m( O7 ?Location equivariance, 位置同变性
8 M ^9 l, H" d! h* w( GLocation invariance, 位置不变性8 @0 s+ T( p# Z) }# F9 T' A
Location scale family, 位置尺度族: x( Q. G+ D! Z* g# E5 g
Log rank test, 时序检验 1 ^( M( g. f9 b5 z
Logarithmic curve, 对数曲线+ l2 A$ j* F5 |7 B
Logarithmic normal distribution, 对数正态分布5 _' |% s8 W9 M0 s! Q
Logarithmic scale, 对数尺度
" U5 Z/ V" ~, F( k' t" ELogarithmic transformation, 对数变换1 l5 E) I- S1 t6 M1 `, F9 t
Logic check, 逻辑检查
" p- t0 o5 p/ d" o. w }0 g LLogistic distribution, 逻辑斯特分布2 N6 [. }* y$ k+ r/ t
Logit transformation, Logit转换; V9 T- w7 c. b* W$ O6 L: e, m8 _
LOGLINEAR, 多维列联表通用模型
" k! F. O6 c- p# X9 Q7 XLognormal distribution, 对数正态分布1 V% |$ t& l) k+ u! q. y3 |$ i
Lost function, 损失函数/ w7 `& r9 v# ?+ _/ t; F
Low correlation, 低度相关5 i- X6 f0 c, Q
Lower limit, 下限
9 V4 x" B& ^# P) ?Lowest-attained variance, 最小可达方差
+ g; p: ]0 f5 f( YLSD, 最小显著差法的简称
; S/ A1 c: z7 @, l, bLurking variable, 潜在变量
/ P+ [- H! T9 e& s5 v# C! r+ IMain effect, 主效应
. A6 [0 o0 ~) K4 L- X1 wMajor heading, 主辞标目
7 s$ F7 p3 F8 D9 GMarginal density function, 边缘密度函数
! N" I& t- k. Z/ Y/ SMarginal probability, 边缘概率
% ^: D6 J3 J/ C; ?. X: D9 m- iMarginal probability distribution, 边缘概率分布
8 m g/ d9 x& Y- xMatched data, 配对资料: g5 l; x m/ z0 C/ u, @( Y
Matched distribution, 匹配过分布6 M# J! C& _1 R& j8 x+ [
Matching of distribution, 分布的匹配8 r. Z3 c, v, P' j% W9 S! H
Matching of transformation, 变换的匹配
- ^% @$ Q& k, HMathematical expectation, 数学期望
! t9 R! ?) V2 k1 VMathematical model, 数学模型
6 o' D5 l) \/ d$ Z1 P! N1 _Maximum L-estimator, 极大极小L 估计量
& M+ t' \1 X$ S. ]. z& iMaximum likelihood method, 最大似然法9 L1 B! N( T% V8 A. q
Mean, 均数
) }" [, Z$ P3 W; \6 |" M0 HMean squares between groups, 组间均方1 f7 y Z; ?/ N
Mean squares within group, 组内均方+ V4 N% w: F2 F5 e2 W. t5 E
Means (Compare means), 均值-均值比较
8 H' m! F0 { T; s. DMedian, 中位数
4 N1 o5 B% K9 uMedian effective dose, 半数效量
0 D5 ?; x( ?* vMedian lethal dose, 半数致死量
: w) k, ]6 o& s$ A+ OMedian polish, 中位数平滑2 I7 S3 v( w7 I+ c4 S
Median test, 中位数检验
Z; D" m5 M6 T1 z, I rMinimal sufficient statistic, 最小充分统计量 J0 h4 N# E* y+ a
Minimum distance estimation, 最小距离估计
- }7 K4 i' o5 m8 ~1 [Minimum effective dose, 最小有效量
; `3 j/ N2 A P& {0 O! O- KMinimum lethal dose, 最小致死量
7 ^7 i" s9 z& }" w7 h$ t [Minimum variance estimator, 最小方差估计量
3 H3 x3 l7 z7 N8 HMINITAB, 统计软件包
+ x/ J7 x* A3 ZMinor heading, 宾词标目; c' X9 u3 H4 M5 _8 ^% m3 |/ P
Missing data, 缺失值' T- U. I; ~4 S
Model specification, 模型的确定
5 `9 `- v$ y5 U5 Y( }- d: n) QModeling Statistics , 模型统计
! q3 n0 x' }9 j/ SModels for outliers, 离群值模型
2 e6 y: h$ t) R M6 EModifying the model, 模型的修正
* e, J5 G$ E3 n0 [Modulus of continuity, 连续性模
8 R6 c0 ^ |/ | j lMorbidity, 发病率
4 F5 b$ r9 d0 m. J% JMost favorable configuration, 最有利构形" H1 m6 T$ r8 N( o; w6 g1 k6 l
Multidimensional Scaling (ASCAL), 多维尺度/多维标度
) s @: Z6 q5 {1 W, zMultinomial Logistic Regression , 多项逻辑斯蒂回归9 D6 [; |. A, l! g
Multiple comparison, 多重比较4 U7 ~5 M G2 s. z1 g
Multiple correlation , 复相关; z* ]& O$ E. O* M1 I2 V% z: [
Multiple covariance, 多元协方差
9 `- Y7 ]8 |9 OMultiple linear regression, 多元线性回归
; v/ x( x' z* nMultiple response , 多重选项
' y; J% f" _8 L. q: T- e7 V9 R, CMultiple solutions, 多解6 o9 Z, v( K0 ]
Multiplication theorem, 乘法定理6 ?# O$ i8 `% r0 l- K4 n
Multiresponse, 多元响应
6 h4 P# G" s1 E+ A6 Z; @3 ^" V; YMulti-stage sampling, 多阶段抽样/ g6 U4 l# }9 y5 l! Q* Z
Multivariate T distribution, 多元T分布& ^ T1 j" g3 u; s# i0 b
Mutual exclusive, 互不相容, X+ M+ h( f) t; h1 S
Mutual independence, 互相独立% w+ Q! Z8 P: x6 p; v8 O. e
Natural boundary, 自然边界# ]! p2 j. p& K3 D& ~0 @; a, @
Natural dead, 自然死亡
& z6 X/ ~% I( v7 ?+ n( f4 fNatural zero, 自然零9 o# S5 \. F5 V- _+ {$ c
Negative correlation, 负相关
0 r9 {/ B* e+ Q! J! BNegative linear correlation, 负线性相关) }9 [* Y& Y" E, T5 e# E( l1 c
Negatively skewed, 负偏0 |# \7 |* c1 d. ~- f6 Z9 z. l0 c
Newman-Keuls method, q检验% J6 |6 T5 Y4 w0 b, @
NK method, q检验
& i5 D5 |- [' h, X6 B% t9 h" y0 @No statistical significance, 无统计意义
1 R# e. a8 t8 j# c5 d, K0 a$ bNominal variable, 名义变量+ {$ W$ o5 ^8 d7 r1 V7 f
Nonconstancy of variability, 变异的非定常性
8 Q# p; C7 c+ t2 ?% dNonlinear regression, 非线性相关9 C/ l+ j- z$ N1 ^) l6 h3 K& F7 W9 \
Nonparametric statistics, 非参数统计 n P1 O7 c# q* Y2 |
Nonparametric test, 非参数检验
5 O9 I+ }% A! _. o0 C# rNonparametric tests, 非参数检验" S8 X4 X6 u5 x5 G' \+ n& R% [- d
Normal deviate, 正态离差
) B/ L" n2 i- U# F* ]Normal distribution, 正态分布; `) l6 [. ^. l; y% B. S4 W
Normal equation, 正规方程组
) f% H; D: F) j7 cNormal ranges, 正常范围
9 Y9 @2 j' d! p+ m; c# \! ?9 _Normal value, 正常值& {' W# u" ], W- i S
Nuisance parameter, 多余参数/讨厌参数) q5 ~) O0 G g' y
Null hypothesis, 无效假设 8 @) C2 K4 [/ d3 _/ E
Numerical variable, 数值变量
7 _0 {+ R/ B ?5 `Objective function, 目标函数$ [- u4 H: ]2 K
Observation unit, 观察单位
2 {/ N/ }1 C5 P, G& _+ T) lObserved value, 观察值2 V3 H5 @; A( K8 ^
One sided test, 单侧检验 ~! B: B( t/ J) F
One-way analysis of variance, 单因素方差分析
. v; [+ w* e; h; `Oneway ANOVA , 单因素方差分析
; t* q$ C' Z0 K- V% @+ UOpen sequential trial, 开放型序贯设计( O& C2 K$ Y# w' D0 q1 l, a4 ^
Optrim, 优切尾+ m: T9 s% M2 v! d2 j
Optrim efficiency, 优切尾效率
( d& B& l& ~+ j5 EOrder statistics, 顺序统计量
/ v' v& V4 b5 G3 C, S- UOrdered categories, 有序分类' Q# I( H# `' J! |8 F1 ~
Ordinal logistic regression , 序数逻辑斯蒂回归
& Y0 H+ f. h7 @! |7 P9 OOrdinal variable, 有序变量( g- s7 }0 ^5 e! M& B1 L3 K3 x
Orthogonal basis, 正交基1 t. V! V5 v" x3 C5 Z+ X
Orthogonal design, 正交试验设计
! H1 R3 |( @0 j2 k8 B# e, q. fOrthogonality conditions, 正交条件6 d+ Q5 u, u) r3 [: @
ORTHOPLAN, 正交设计 6 Y& z% {8 ?+ b4 w5 F
Outlier cutoffs, 离群值截断点
6 h f0 F; c0 d6 }' J$ aOutliers, 极端值
# o& L3 d$ K- ]9 fOVERALS , 多组变量的非线性正规相关 " n( y Y @) K* b) t+ y
Overshoot, 迭代过度 ]" s% |( V* ?; E7 c
Paired design, 配对设计
2 _, B( a5 t- R3 r9 |! n7 HPaired sample, 配对样本$ V1 U) P) D0 E( l
Pairwise slopes, 成对斜率
6 s' ?4 p/ \5 {8 x, _Parabola, 抛物线. ]8 L9 i { M# n8 h. e
Parallel tests, 平行试验0 _9 J; L% \! @2 B1 F& w
Parameter, 参数. B- d" {2 d5 J
Parametric statistics, 参数统计: Y4 D/ t3 k- e- S2 x
Parametric test, 参数检验% v: f/ f/ |& U3 j+ L8 |
Partial correlation, 偏相关, t9 ]$ o# h- f6 t& p5 ~7 y
Partial regression, 偏回归
) Q% f# C3 l T/ {" o& @! cPartial sorting, 偏排序* v! Z# v& z( D) A: p# ]; X
Partials residuals, 偏残差
( w Y; A6 L. t# YPattern, 模式
2 Z( x8 f; v9 k2 u9 \4 APearson curves, 皮尔逊曲线; @# @5 x2 ]% h8 }# W
Peeling, 退层
- v; E8 J! v8 |3 NPercent bar graph, 百分条形图
5 E4 k5 S, [4 P* s. APercentage, 百分比5 [8 `$ L1 F0 ]. R1 @$ I
Percentile, 百分位数' Y8 h3 f Z$ [ Z
Percentile curves, 百分位曲线
1 d6 E* f" B0 a; DPeriodicity, 周期性
9 d' b( t% o" k& zPermutation, 排列. f' P, ]) h' s" x( o4 [
P-estimator, P估计量3 p( J/ T# T# d* ^( A s
Pie graph, 饼图
. K& l: f& t( X. q( hPitman estimator, 皮特曼估计量! b0 @5 [) P9 y8 }
Pivot, 枢轴量# D j& Y9 t! O! Z# u
Planar, 平坦9 ?; o8 V9 ?# q$ Y0 k8 l
Planar assumption, 平面的假设2 t( {$ h% h" d5 [
PLANCARDS, 生成试验的计划卡
5 Y3 } c1 r. u6 ~Point estimation, 点估计' A' x- ~7 S3 R- W, q7 I
Poisson distribution, 泊松分布
7 j) k1 P |" Z1 MPolishing, 平滑* E- H0 w" `; @2 ^3 ~2 u" X5 t
Polled standard deviation, 合并标准差
/ T$ V$ y% z. {1 JPolled variance, 合并方差
& V' U9 \ M, GPolygon, 多边图1 j+ h! J" P2 M
Polynomial, 多项式
, V1 w$ Q# s" H. v+ b, r6 K9 E6 S% `Polynomial curve, 多项式曲线; R$ g" |2 V* _/ C# N4 }) y! W
Population, 总体
0 f N; I. C7 G$ xPopulation attributable risk, 人群归因危险度
7 o( C* q8 u7 f! yPositive correlation, 正相关
) A4 ^' o# g( ]4 h" ?1 D3 N: E7 [Positively skewed, 正偏& m3 O3 T# d8 `/ P' I2 s) ?
Posterior distribution, 后验分布7 Z7 O9 u$ S. G: i! a0 M
Power of a test, 检验效能2 s: q' h3 f& g1 }
Precision, 精密度
! ]6 H' c0 ]/ uPredicted value, 预测值
# l! d: g0 p% I0 M1 M& E7 i+ TPreliminary analysis, 预备性分析; o- V) n0 k- B7 M4 E! H$ v
Principal component analysis, 主成分分析
# T Z# b! c1 m) c+ sPrior distribution, 先验分布
2 V1 d6 ^; L5 J" N0 m. F1 x* g; sPrior probability, 先验概率
7 g9 J {/ j$ H" v& hProbabilistic model, 概率模型2 X/ L7 l0 l: }0 d7 A
probability, 概率8 v! B3 H" G( Y& H/ F& z' G
Probability density, 概率密度
7 j, A, K$ u( W( Y9 @; h: _Product moment, 乘积矩/协方差: f s t9 B# V P* t" |
Profile trace, 截面迹图/ V: p+ b* c+ j. h
Proportion, 比/构成比
' y) x- p! j& \; D. TProportion allocation in stratified random sampling, 按比例分层随机抽样5 m7 u3 Y7 A% \- S1 d9 n
Proportionate, 成比例9 D! L$ ^: ?: l
Proportionate sub-class numbers, 成比例次级组含量1 ]. c/ F/ X/ |2 D# b; |
Prospective study, 前瞻性调查
0 r! n, T( i. |8 S+ pProximities, 亲近性
( H a% W. T# F8 KPseudo F test, 近似F检验
: }8 y/ g* m2 ]7 V( s3 EPseudo model, 近似模型' B3 V; ^( [8 F" v, b& P
Pseudosigma, 伪标准差+ \5 i& G1 N( ^/ U* `8 Q0 N; a$ B
Purposive sampling, 有目的抽样. Y' I x- @; u. ?" D
QR decomposition, QR分解
- w+ ?9 W. m, i1 S6 SQuadratic approximation, 二次近似0 j/ ^) `9 x/ @( q7 [0 v: d, n) E
Qualitative classification, 属性分类
) l% H) t6 j9 A% t/ v& ~8 O7 S' QQualitative method, 定性方法4 h4 D2 r$ B, K) X0 ?% c7 w
Quantile-quantile plot, 分位数-分位数图/Q-Q图
, R+ v" V: H) z/ oQuantitative analysis, 定量分析
" B" R7 u- P& m9 V9 T" o0 wQuartile, 四分位数5 m( b& E: `8 L' k: K0 {
Quick Cluster, 快速聚类8 O8 B" n+ y, P- ~2 g
Radix sort, 基数排序; H; }( d, E; x
Random allocation, 随机化分组% i4 \6 q; B/ l0 _) O8 Y/ [+ C% n; u
Random blocks design, 随机区组设计
9 T0 H# ?+ V' \, c0 pRandom event, 随机事件" F% T% ]. r) s4 ]- _3 Q
Randomization, 随机化
6 R5 ~6 z7 _& c7 s, L9 X1 iRange, 极差/全距
6 o# Y. [) n- M9 Z7 E) HRank correlation, 等级相关: Q- g6 N- g: u
Rank sum test, 秩和检验; c' M$ L2 f# n( k; N `. S1 {
Rank test, 秩检验
* \+ }/ a3 D& f; s/ jRanked data, 等级资料
6 l% v3 Y2 c6 pRate, 比率
1 B2 u4 D( _: R6 QRatio, 比例; D; q( d* I T/ i6 K4 s4 I+ T
Raw data, 原始资料
* a& X4 V) ` w( jRaw residual, 原始残差$ A' p$ L* A _2 }) `* ]: _. I
Rayleigh's test, 雷氏检验
1 _4 H0 @: h; K( H. TRayleigh's Z, 雷氏Z值 % E# o6 l+ Y5 y- o V; D4 A! m y
Reciprocal, 倒数6 Z$ I5 G: p+ l/ Q. D& u" K
Reciprocal transformation, 倒数变换1 N1 t, w; o- R7 x4 _2 v5 e
Recording, 记录
" v# z: J0 s! H, ~/ {6 u* Q. o7 cRedescending estimators, 回降估计量7 w. J4 B8 |5 s* t8 z- Z4 N
Reducing dimensions, 降维! k; w" T/ x j' g
Re-expression, 重新表达
! W/ `3 w# V+ h( MReference set, 标准组
( p/ N* B% x5 V( JRegion of acceptance, 接受域, V0 m+ T9 k1 b( t: |
Regression coefficient, 回归系数
, Z3 F6 T8 e+ v m, g! s3 `Regression sum of square, 回归平方和
5 H3 u" ?- S2 h- f/ B- p- q0 XRejection point, 拒绝点
2 s% C6 b+ ^+ R- lRelative dispersion, 相对离散度, {. c5 X& C0 f$ v
Relative number, 相对数
- A1 R( a7 ^4 W8 \Reliability, 可靠性
: l: A! ]9 E& k( {% K8 \9 DReparametrization, 重新设置参数0 d+ N9 W- F/ l6 t
Replication, 重复: d- T1 N. b! @( S/ d `8 Y
Report Summaries, 报告摘要9 N6 G+ w# u1 F/ v6 u, k
Residual sum of square, 剩余平方和
5 p# a' X0 r/ O& Z- W1 FResistance, 耐抗性; U6 [4 S* Z0 }$ m
Resistant line, 耐抗线1 H$ F" P. M& g
Resistant technique, 耐抗技术: A* ^$ {% }1 C; E6 g5 j
R-estimator of location, 位置R估计量+ c+ e5 `2 V3 @7 @
R-estimator of scale, 尺度R估计量/ C. @! [2 \- F d+ ?6 N2 z
Retrospective study, 回顾性调查
5 s; H G( v1 j" w/ QRidge trace, 岭迹+ F9 \1 J; K/ u- _# A q1 u; b! D
Ridit analysis, Ridit分析$ l# O$ e* g3 ]) b; n: t3 Z
Rotation, 旋转9 ^5 ~) E0 Q. ~
Rounding, 舍入
$ Q( K2 T; x& X+ P# ]' ]9 G# tRow, 行
) [- |0 J$ P9 \( |3 v' nRow effects, 行效应. h$ [5 t/ Q* G8 T. B# t
Row factor, 行因素
& f9 A: }+ J6 j# A/ y: tRXC table, RXC表
% L6 e' v4 ]6 ~* \. |$ PSample, 样本
9 B: |- ]( y7 j/ SSample regression coefficient, 样本回归系数
. `9 D) W& o7 {) y) NSample size, 样本量# O' m2 |5 L: j
Sample standard deviation, 样本标准差% j9 l2 B. [6 e2 y
Sampling error, 抽样误差! c |8 U, ], b1 b1 J( B
SAS(Statistical analysis system ), SAS统计软件包
+ j- r3 B! N1 \! B/ AScale, 尺度/量表3 [, u) J# ^; U4 a* \6 \% x
Scatter diagram, 散点图
3 d8 [/ ?' o! B2 \& V* [Schematic plot, 示意图/简图. m2 s! H. Y: {
Score test, 计分检验
. C) s# `# g! q* FScreening, 筛检
* p0 @/ E5 @* LSEASON, 季节分析 ' I& f. B# j5 f2 u
Second derivative, 二阶导数4 s! y8 x7 Y6 j& b) C+ V
Second principal component, 第二主成分0 w0 V7 Z' {6 M. m
SEM (Structural equation modeling), 结构化方程模型 4 t" M: [7 M; k' Q; @
Semi-logarithmic graph, 半对数图+ q! |: ~# \# J' B y
Semi-logarithmic paper, 半对数格纸
) {4 K5 b* Y# L1 x* e8 j* Y! GSensitivity curve, 敏感度曲线
" k# G( g0 p2 K* ySequential analysis, 贯序分析
( s, b# R- |, A# U1 e, w- n/ O( Q2 gSequential data set, 顺序数据集
6 W, J2 \3 s6 }$ QSequential design, 贯序设计2 q$ |( O- o" h" E; Y
Sequential method, 贯序法( P5 N. ^3 j r
Sequential test, 贯序检验法
' P1 Z1 \6 I; N' B( n5 R; h$ h1 ]8 PSerial tests, 系列试验 s- n! W5 y" K: f) e' R" w2 S; U8 J
Short-cut method, 简捷法
) Y# p' g% l! Y3 ?4 ?7 l9 ^- t) ASigmoid curve, S形曲线' C1 {, j+ Z8 C0 F3 M
Sign function, 正负号函数. s% e* n; ^% f) k$ [/ [. b
Sign test, 符号检验; ?- D5 J" m6 c" B7 q
Signed rank, 符号秩
, ?' k! v" z) z/ p3 l1 XSignificance test, 显著性检验
5 B# T3 g% o) _7 x$ A$ hSignificant figure, 有效数字
- P) M% Z8 t0 j1 ]0 m; J+ y4 K1 aSimple cluster sampling, 简单整群抽样
$ A/ w/ R! z- N4 D( g( USimple correlation, 简单相关; u8 S: c' P. T
Simple random sampling, 简单随机抽样/ b: z+ Y' w0 K7 z7 F# @
Simple regression, 简单回归
$ `% S' \% {! Msimple table, 简单表
' P+ S+ s+ J& e& O" w# @- C9 tSine estimator, 正弦估计量* B' k; |0 M8 w7 r% J
Single-valued estimate, 单值估计
_8 _+ Y+ K# `- R. QSingular matrix, 奇异矩阵
0 `, X: C, r2 `1 q- b, }Skewed distribution, 偏斜分布# M" V8 k! s5 u# J# P
Skewness, 偏度+ b8 B6 d. Y; t( [- N
Slash distribution, 斜线分布
/ |: Q, K5 L; `8 J; O V/ N. [Slope, 斜率
, r+ s7 H5 D4 `, ISmirnov test, 斯米尔诺夫检验: W7 V5 E8 _4 E7 s6 ?+ o4 Q1 u) q* A
Source of variation, 变异来源
- U7 h3 i9 W. P0 ?Spearman rank correlation, 斯皮尔曼等级相关, U7 j3 e/ s3 I
Specific factor, 特殊因子, ^. T3 k# b# w5 T; {
Specific factor variance, 特殊因子方差
: b1 @( Q) J$ U' ^* ]% DSpectra , 频谱. Q" s6 V8 Y9 Q3 @9 x; M* G R7 ?
Spherical distribution, 球型正态分布# a' A4 H% K* w0 L: t
Spread, 展布! \" N/ r: u! D5 [ N) K: l
SPSS(Statistical package for the social science), SPSS统计软件包
5 F- |1 d( m% X* R9 fSpurious correlation, 假性相关
6 ?) M/ S- o7 mSquare root transformation, 平方根变换/ X& l/ {3 Y. ?/ r
Stabilizing variance, 稳定方差5 _& {* j/ ?) u. R. x
Standard deviation, 标准差
~0 X" |! u( R" @/ kStandard error, 标准误' y/ \. ~( Q* _" |- A+ m
Standard error of difference, 差别的标准误- V: z' H/ t/ j+ b
Standard error of estimate, 标准估计误差
/ K9 ^3 s6 d6 S pStandard error of rate, 率的标准误6 W R% ~7 }4 l4 K* C9 R3 A7 G
Standard normal distribution, 标准正态分布$ S. P( m% }7 r& U9 B
Standardization, 标准化4 Q0 `- f; `9 i0 V6 D7 V D: w I
Starting value, 起始值: v4 I( H( m. G0 S! y7 q
Statistic, 统计量
7 ?! v8 z/ B) R% e# g, S9 |Statistical control, 统计控制
+ b3 G! J4 P5 x* K& KStatistical graph, 统计图
9 b: K. W2 v: [2 G4 m) w3 JStatistical inference, 统计推断$ I6 `6 n4 {5 u8 @' D* r8 f
Statistical table, 统计表
* g" D1 V4 q" Z3 k! @% T2 wSteepest descent, 最速下降法1 [( K2 Y$ ~- u, M2 u
Stem and leaf display, 茎叶图
' M! b' c6 g! N5 H& [ DStep factor, 步长因子/ K6 M' L [+ l$ u4 R
Stepwise regression, 逐步回归
) F. I7 A6 ?4 s% V( ?Storage, 存1 ?, P: f2 [ j d6 a! o* U
Strata, 层（复数）
+ `( s, W: |8 D/ w# gStratified sampling, 分层抽样$ z; ^+ a+ `4 f$ H' i
Stratified sampling, 分层抽样 G4 X& Z+ R% U# L
Strength, 强度4 r5 ] ^1 z+ v
Stringency, 严密性
5 P7 O; K( A. X: j% b# zStructural relationship, 结构关系
; Z" b2 v5 P# M& M' F( \Studentized residual, 学生化残差/t化残差- K# {# l. X a" d! X' e
Sub-class numbers, 次级组含量5 t9 s9 n2 G' ^ ]0 w& t5 {/ N6 S
Subdividing, 分割
; g1 N% t7 a4 T, Z* e1 cSufficient statistic, 充分统计量8 @/ T0 Z x; L+ {; ?8 c* [
Sum of products, 积和! ]* [$ d, P3 n( T6 Z
Sum of squares, 离差平方和- I+ F5 h' y. l9 Y2 T& |7 ]
Sum of squares about regression, 回归平方和
- Q+ ~# W; C2 y, F9 @# ~Sum of squares between groups, 组间平方和
7 E! W& S0 P0 X' T; T0 XSum of squares of partial regression, 偏回归平方和
+ t$ V. K6 `- d2 O, V# Z% VSure event, 必然事件3 c2 k& z) }0 j) P5 R$ N
Survey, 调查1 D$ S) b/ K' v6 a, P8 j
Survival, 生存分析
3 i/ e7 @0 p$ w- w1 A& ySurvival rate, 生存率
' _# X' x! g! w2 `" GSuspended root gram, 悬吊根图
0 A8 P( R& M3 ^( F1 Z; lSymmetry, 对称' ~5 F, s' x k" ^6 _# U
Systematic error, 系统误差/ y3 Z( q3 @( N- z' B; G# r: C
Systematic sampling, 系统抽样
( z: p) @5 a) b8 y, c4 X$ Y8 vTags, 标签( F/ W( y Y0 E& b" N
Tail area, 尾部面积
2 D5 m+ x0 q+ D% lTail length, 尾长
/ g( M _+ |+ q- P/ F" @9 S. eTail weight, 尾重
4 C4 o% \5 J* UTangent line, 切线
: T% s/ G0 J( i6 }9 U) S2 b1 ITarget distribution, 目标分布- U- `6 Q+ i) `% } k7 p
Taylor series, 泰勒级数8 ^3 }: `% Z: M
Tendency of dispersion, 离散趋势* ~$ n d; D; F5 v, L9 q
Testing of hypotheses, 假设检验. z) X* n% o8 g4 l7 e* V2 R; M
Theoretical frequency, 理论频数4 N9 u l2 c) m
Time series, 时间序列
7 M Q! c2 H4 Q0 c6 {) E' k: e- p* jTolerance interval, 容忍区间" z6 T6 p2 I- o r# ^4 l2 F; _" k# `
Tolerance lower limit, 容忍下限
# k( ?3 W" ?; [# jTolerance upper limit, 容忍上限
) i8 x4 ~- J: ~. g+ nTorsion, 扰率" k" D0 j( G& g3 N
Total sum of square, 总平方和
/ e$ y5 D: G8 ^8 `9 e% N/ KTotal variation, 总变异( Y4 Y: ~3 M1 i$ w7 _+ [, D- t
Transformation, 转换
4 r4 ~4 d6 X( u* A; z( V5 }Treatment, 处理
6 j, `) A$ w# W; J% zTrend, 趋势8 ~! p8 o$ h( H3 s9 Z( E( @$ x
Trend of percentage, 百分比趋势
# ^ j& L' X+ V; ?5 \7 g, nTrial, 试验* L6 Q& {4 s& L5 c* x, L
Trial and error method, 试错法8 c+ ] T+ c4 l: @7 o& R$ @
Tuning constant, 细调常数
- a. E, D$ @* eTwo sided test, 双向检验
" n% d$ L, s2 {; i+ U9 k9 eTwo-stage least squares, 二阶最小平方
# P0 d+ l* R( Y( {/ w2 ~% s! y2 kTwo-stage sampling, 二阶段抽样0 _' R% I7 h. k" t
Two-tailed test, 双侧检验" I8 U6 F( a' k
Two-way analysis of variance, 双因素方差分析# U1 q7 a4 G+ `) I- c& y
Two-way table, 双向表
9 \" Y" N1 R1 b( v$ [. V+ WType I error, 一类错误/α错误/ j' c) I* N+ g# _9 R" k
Type II error, 二类错误/β错误
: P: q$ a' C) Z H' N8 W8 TUMVU, 方差一致最小无偏估计简称
" z7 }' _& g" W* d' kUnbiased estimate, 无偏估计% J5 n/ Y9 G$ b. h
Unconstrained nonlinear regression , 无约束非线性回归 k6 E( w$ V ~( n+ J I# }4 L) w0 Z
Unequal subclass number, 不等次级组含量
+ ?& {& f' p4 V% }0 QUngrouped data, 不分组资料9 n8 D' w; K+ e9 C* v- I
Uniform coordinate, 均匀坐标
. g/ |4 d* M# t$ T/ ?Uniform distribution, 均匀分布4 M; L) w( l* u
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计; n. V9 s3 t' B' O p
Unit, 单元
# z0 E8 u; ]% z$ ZUnordered categories, 无序分类
- h; _) {: \, w5 EUpper limit, 上限) I M( Y" W$ \6 k" v( _; }1 C
Upward rank, 升秩0 Z) H0 v# {, n7 ^
Vague concept, 模糊概念3 f5 ?- x& f6 A* t
Validity, 有效性/ Y* P2 E- u& @9 G
VARCOMP (Variance component estimation), 方差元素估计2 Q' e' j7 x: M1 h8 v
Variability, 变异性0 U9 b% n( ~6 j$ o3 o/ N
Variable, 变量
7 K) b8 F: c+ lVariance, 方差. k9 B/ P! Q* ~ b& R
Variation, 变异
' c- t7 ?9 S1 g5 a" @) U6 sVarimax orthogonal rotation, 方差最大正交旋转0 n9 f' ?4 S2 i: |$ e8 X; } a
Volume of distribution, 容积
) s7 B% `; ]( p+ `$ @1 F, YW test, W检验, s& k8 e. Q8 o3 K4 {0 D
Weibull distribution, 威布尔分布
4 ^. Z" r% ?1 C8 k# QWeight, 权数; z9 _9 P6 g1 H+ E: _9 B) U5 j
Weighted Chi-square test, 加权卡方检验/Cochran检验
& X: o, e* q1 x# d1 e1 QWeighted linear regression method, 加权直线回归. S# z6 o- c# z' i, j
Weighted mean, 加权平均数
) \( n* u& j# S9 J5 Z, yWeighted mean square, 加权平均方差; Y% _% ~* W# `" V" h4 S: Q- e
Weighted sum of square, 加权平方和/ e6 B- P! v3 D8 T D; J0 T
Weighting coefficient, 权重系数
$ X" m0 r( W% y# v2 O7 Z2 L" CWeighting method, 加权法 ) s4 b1 r& G3 @' I
W-estimation, W估计量& B p3 k8 {3 y/ w4 Y4 _8 L
W-estimation of location, 位置W估计量" T4 K" k9 T" m8 S0 |$ J& q3 x/ z
Width, 宽度
0 l' e6 C# H( s- ]Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验
) w# r+ p9 P) s6 M" R: u2 W! a$ iWild point, 野点/狂点5 M9 H& n" {0 P
Wild value, 野值/狂值! a) U% }+ p# w9 o9 x
Winsorized mean, 缩尾均值
. M2 d' A/ Q+ |8 ]Withdraw, 失访 " ^- s- g9 w7 P
Youden's index, 尤登指数' P0 h# H$ b4 H2 |3 l
Z test, Z检验8 y g. k" R! Q- N, b3 g
Zero correlation, 零相关: U! p2 L# S5 `: p( C8 M
Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
